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data-Driven Method for Predicting Remaining Useful Life of Bearings Based on Multi-Layer perception Neural Network and Bidirectional Long Short-Term Memory Network

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Structural Durability & Health Monitoring 2025年第2期19卷 365-383页

作者： Yongfeng Tai Xingyu Yan Xiangyi Geng Lin Mu Mingshun Jiang Faye Zhang CRRC Qingdao Sifang Co. Ltd.Qingdao266111China School of control Science and engineering Shandong UniversityJinan250061China public(Innovation)Experimental Teaching center Shangdong UniversityQingdao266237China engineering Training center Shangdong UniversityJinan250061China

The remaining useful life prediction of rolling bearing is vital in safety and reliability *** engineering scenarios,only a small amount of bearing performance degradation data can be obtained through accelerated life *** the absence of lifetime data,the hidden long-term correlation between performance degradation data is challenging to mine effectively,which is the main factor that restricts the prediction precision and engineering application of the residual life prediction *** address this problem,a novel method based on the multi-layer perception neural network and bidirectional long short-term memory network is ***,a nonlinear health indicator(HI)calculation method based on kernel principal component analysis(KPCA)and exponential weighted moving average(EWMA)is ***,using the raw vibration data and HI,a multi-layer perceptron(MLP)neural network is trained to further calculate the HI of the online bearing in real ***,The bidirectional long short-term memory model(BiLSTM)optimized by particle swarm optimization(PSO)is used to mine the time series features of HI and predict the remaining service *** verification experiments and comparative experiments are carried out on the XJTU-SY bearing open *** research results indicate that this method has an excellent ability to predict future HI and remaining life.

关键词： Remaining useful life prediction rolling bearing health indicator construction multilayer perceptron bidirectional long short-term memory network

Video Stabilization via Prediction with Time-Series Network and Image Inpainting with Pyramid Fusion

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Chinese Journal of Electronics 2021年第6期30卷 1103-1110页

作者： CHENG Keyang LI Shichao RONG Lan WANG Wenshan SHI Wenxi ZHAN Yongzhao School of Computer Science and Communication engineering Jiangsu University Jiangsu Province big data Ubiquitous perception and Intelligent Agricultural Application engineering research center Cyber Space Security Academy of Jiangsu University national engineering Laboratory for public safety risk perception and control by big data Xinjiang Lianhaichuangzhi Information Technology Co. Ltd.

Due to the poor filling effect of the video image defect commonly used in the video stabilization field, the video is seemed still unstable after the image stabilization process, which seriously affects the visual effect. To solve this problem, we improve a video stabilization method based on time-series network prediction and pyramid fusion restoration is proposed to optimize the visual effect after image *** flow of the proposed method is as follows: First,it is adaptive to determine whether the defect of the corresponding frame at the current time needs padding inpainting. Then, for the frame that needs to be inpainting,the frames generated before the current moment are sent to the model combining the convolutional neural networks and the gate recurrent unit to predict the part to be filled. Next the current defect image and the complete image to be filled are brought into the Laplacian pyramid reconstruction, and the improved weighted optimal suture is introduced for splicing during the fusion. Finally, the video frame is cut after reconstruction. The method is tested on a data set composed of videos commonly used in the field of video stabilization. The experimental results show that the average peak signal to noise ratio of the method is 2 to 5 d B higher than that of the comparison algorithm, and the average structural similarity index is improved by about 2% to 7% compared with the contrast algorithm.

关键词： image restoration image sequences video frame cutting improved weighted optimal suture gate recurrent unit video signal processing video stabilization method image fusion Laplacian pyramid reconstruction padding inpainting image resolution neural nets convolutional neural networks video image defect pyramid fusion restoration image inpainting visual effect optimization image reconstruction time-series network prediction image stabilization process

Intelligent proportioning model of converter scrap based on optimization algorithm

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Progress in Natural Science:Materials International 2024年第1期34卷 37-44页

作者： Chaojie Zhang Jinjun Cheng Liqiang Zhang Yingxue Wang Wei Zhang Jianwei Yuan Haichuan Wang School of Metallurgical engineering Anhui University of Technology national engineering research center for public safety risk perception and control by big data(RPP) China Academic of Electronics and Information Technology Wuhu Xinxing Pipes Co. Ltd.

Scrap is one of the main raw materials in converter steelmaking. Due to the wide variety of scrap and the significant differences in its prices, the proportioning of scrap presents a challenge in converter steelmaking. This paper explores the optimal proportioning method of scrap for converters using an optimization mathematical model. Initially, the melting characteristics of scrap after being added to the converter's molten iron were investigated using finite element numerical simulations. The study found that when the weight of the scrap is fixed, both the shape and type of the scrap significantly influence the melting time. Subsequently, employing mathematical optimization methods and considering comprehensive process parameters of the 210t converter smelting, including the composition and unit price of the scrap, as well as the requirements of the converter steelmaking process for scrap, an optimization model for the proportioning of scrap in converters was *** model was solved using computer programming languages. Through this optimization model, it is possible to obtain the lowest cost per ton of molten steel in the converter smelting process by determining the optimal proportions of various types of scrap.

关键词： scrap proportioning Optimization model Converter steelmaking mathematical model numerical simulation

Calibration of the Solar X-ray Detector on-board the Macao Science Satellite-1B for Soft X-ray Detection

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Science China Earth Sciences 2025年第1期68卷 11-26页

作者： Man-Hei NG Xiaoping ZHANG Jianwu CHEN Yongqiang SHI Fuchang ZUO Wenxi PENG Weichun FU Liansheng LI Pengwei LUO Chi-Long TANG Guozheng ZHANG Zhiwu MEI Li WANG Cunhui LI Jiaming OU Yanyan Xu State Key Laboratory of Lunar and Planetary Sciences Macao University of Science and TechnologyMacao999078China Space Optoelectronic Measurement and perception Laboratory Beijing Institute of Control EngineeringBeijing100190China Institute of High Energy Physics Chinese Academy of SciencesBeijing100049China Science and Technology on Vacuum Technology and Physics Laboratory Lanzhou Institute of PhysicsLanzhou730000China China national Space Administration(CNSA) Macao Center for Space Exploration and ScienceMacao999078China

The Solar X-ray Detector(SXD)on-board the Macao Science Satellite-1B(MSS-1B)was successfully launched via the Chinese Long March-2C rocket on 21 May 2023,and commenced operations in early June of the same *** MSS-1B/Soft X-ray Detection Units(SXDUs)employ two silicon drift detectors(SDDs),providing a wide range of energy spectra spanning from 0.7 to 24 ***,the SXDUs deliver a high-resolution capability of 0.14 keV@5.9 keV and operate with a time cadence of 1 ***,we perform thorough calibrations of the MSS-1B/SXDUs,employing a combination of ground experiments and *** addition,quantitative analysis comparing the flux measurements obtained by the MSS-1B/SXDUs to the data collected by the Geostationary Operational Environmental Satellite(GOES),provides compelling evidence of their ***,the preliminary spectral analysis results showcase the robustness and expected performance of the MSS-1B/SXDUs,unlocking their potential for facilitating the study of dynamic evolution of solar ***,the innovative MSS-1B/Solar X-ray Detector facilitates concurrent observations of solar soft and hard X-rays,thereby making valuable contributions to the advancements in solar research.

关键词： Macao Science Satellite-1B(MSS-1B) Calibration Solar X-Ray Detector Spectrometer Soft X-rays Solar flares Solar abundances

Will Crash Experience Affect Driver’s Behavior? An Observation and Analysis on Time Headway Variation Before and After a Traffic Crash

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Tsinghua Science and Technology 2020年第4期25卷 471-478页

作者： Yun Yue Zi Yang Xin Pei Hongxin Chen Chao Song Danya Yao Department of Automation Tsinghua UniversityBeijing 100084China national engineering Laboratory for public safety risk perception and control by big data(PSRPC) China Academy of Electronics and Information TechnologyBeijing 100041China

research into the impact of road accidents on drivers is essential to effective post-crash ***,due to limited data and resources,the current research focus is mainly on those who have suffered severe *** this paper,we propose a novel approach to examining the impact that being involved in a crash has on drivers by using traffic surveillance *** traffic video surveillance systems,the locations of vehicles at different moments in time are captured and their headway,which is an important indicator of driving behavior,can be calculated from this *** was found that there was a sudden increase in headway when drivers return to the road after being involved in a crash,but that the headway returned to its pre-crash level over *** further analyzed the duration of the decay using a Cox proportional hazards regression model,which revealed many significant factors(related to the driver,vehicle,and nature of the accident)behind the survival time of the increased *** approach is able to reveal the crash impact on drivers in a convenient and economical *** can enhance the understanding of the impact of a crash on drivers,and help to devise more effective re-education programs and other interventions to encourage drivers who are involved in crashes to drive more safely in the future.

关键词： crash impact driving behavior time headway survival time Cox proportional hazards model

Transportation Mode Identification with GPS Trajectory data and GIS Information

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Tsinghua Science and Technology 2021年第4期26卷 403-416页

作者： Ji Li Xin Pei Xuejiao Wang Danya Yao Yi Zhang Yun Yue Department of Automation Tsinghua UniversityNational Laboratory for Information Science and Technology(TNList)Tsinghua UniversityBeijing 100084China national engineering Laboratory for public safety risk perception and control by big data(NEL-PSRPC) Beijing 100041China

Global Positioning System(GPS) trajectory data can be used to infer transportation modes at certain times and locations. Such data have important applications in many transportation research fields, for instance,to detect the movement mode of travelers, calculate traffic flow in an area, and predict the traffic flow at a certain time in the future. In this paper, we propose a novel method to infer transportation modes from GPS trajectory data and Geographic Information System(GIS) information. This method is based on feature extraction and machine learning classification algorithms. While using GIS information to improve inference accuracy, we ensure that the algorithm is simple and easy to use on mobile devices. Applied to GeoLife GPS trajectory dataset, our method achieves 91.1% accuracy while inferring transportation modes, such as walking, bike, bus, car, and subway, with random forest classification algorithm. GIS features in our method improved the overall accuracy by 2.5% while raising the recall of the bus and subway transportation mode categories by 3.4% and 18.5%. We believe that many algorithms used in detecting the transportation modes from GPS trajectory data that do not utilize GIS information can improve their inference accuracy by using our GIS features, with a slight increase in the consumption of data storage and computing resources.

关键词： transportation mode Global Positioning System(GPS) Geographic Information System(GIS) random forest

Judgment of blast furnace iron-tapping status based on data differential processing and dynamic window analysis algorithm

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Progress in Natural Science:Materials International 2023年第4期33卷 450-457页

作者： Youcheng Zong Zixian Wang Xiang Liu Yi Nian Jianian Pan Chaojie Zhang Yingxue Wang Jianhua Chu Liqiang Zhang The Intelligent Metallurgy research Institute School of Metallurgical Engineering Anhui University of Technology Department of Technical Quality Manufacturing Management Division(Technical Center) Anhui Changjiang Steel Co. Ltd. national engineering research center for public safety risk perception and control by big data(RPP) China Academic of Electronics and Information Technology

Ironmaking plants hold a core position in steel production. Efficient level detection and iron-tapping status judgment can accurately measure the liquid level and predict the amount of molten iron in the ladle, thereby ensuring production safety and improving production efficiency. At present, the judgment of the start and end statuses of blast furnace iron-tapping mainly relies on manual visual inspection. However, due to the high-temperature environment on-site and interference from iron powder, gunning mud, and other dust, operators find it challenging to make accurate judgments. To address these issues, this study proposes a robust and accurate method for judging the iron-tapping status of blast furnaces. This study collected four million on-site liquid level data, underwent interpolation, noise reduction, normalization, and other preprocessing steps, and then used differential processing to calculate the iron-tapping rate. Combined with dynamic window feature analysis, it effectively captured the change characteristics of the liquid level in the ladle under different iron-tapping *** simulated on-site experiments, the method achieved a 96.6 % accuracy rate for iron-tapping status *** real-time iron-tapping status judgment method based on differential processing of liquid level data and dynamic window feature analysis proposed in this study demonstrates high precision and robustness in the complex environment of ironmaking plants. This technology not only improves the production efficiency of the iron and steel link but also frees on-site operators from the harsh working environment, eliminating human errors in judgments and omissions, further promoting the intelligent process of ironmaking plants.

关键词： Blast furnace iron-tapping Molten iron level Radar level gauge Iron-tapping status judgment data differential processing Sliding window

Interpretable Machine Learning Method for Compressive Strength Prediction and Analysis of Pure Fly Ash-based Geopolymer Concrete

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 65-78页

作者： SHI Yuqiong LI Jingyi ZHANG Yang LI Li Key Laboratory of Agricultural Soil and Water engineering in Arid and Semiarid Areas of Ministry of Education Northwest A&F Uni-versityYangling 712100China College of Water Resources and Architectural engineering Northwest A&F UniversityYangling 712100China Chongqing Key Laboratory of public big data Security Technology Chongqing 401420China Chongqing College of Mobile Communication Chongqing 401520China Department of Civil and Environmental engineering The Hong Kong Polytechnic UniversityHung HomKowloonHong KongChina national Rail Transit Electrification and Automation engineering Technology research center(Hong Kong Branch) The Hong Kong Polytechnic UniversityKowloonHung HomHong KongChina

In order to study the characteristics of pure fly ash-based geopolymer concrete(PFGC)conveniently,we used a machine learning method that can quantify the perception of characteristics to predict its compressive *** this study,505 groups of data were collected,and a new database of compressive strength of PFGC was *** order to establish an accurate prediction model of compressive strength,five different types of machine learning networks were used for comparative *** five machine learning models all showed good compressive strength prediction performance on *** them,R2,MSE,RMSE and MAE of decision tree model(DT)are 0.99,1.58,1.25,and 0.25,*** R2,MSE,RMSE and MAE of random forest model(RF)are 0.97,5.17,2.27 and 1.38,*** two models have high prediction accuracy and outstanding generalization *** order to enhance the interpretability of model decision-making,we used importance ranking to obtain the perception of machine learning model to 13 *** 13 variables include chemical composition of fly ash(SiO_(2)/Al_(2)O_(3),Si/Al),the ratio of alkaline liquid to the binder,curing temperature,curing durations inside oven,fly ash dosage,fine aggregate dosage,coarse aggregate dosage,extra water dosage and sodium hydroxide *** temperature,specimen ages and curing durations inside oven have the greatest influence on the prediction results,indicating that curing conditions have more prominent influence on the compressive strength of PFGC than ordinary Portland cement *** importance of curing conditions of PFGC even exceeds that of the concrete mix proportion,due to the low reactivity of pure fly ash.

关键词： machine learning pure fly ash geopolymer compressive strength feature perception

Changes in factor profiles deriving from photochemical losses of volatile organic compounds:Insight from daytime and nighttime positive matrix factorization ana

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Journal of Environmental Sciences 2025年第5期151卷 627-639页

作者： Baoshuang Liu Tao Yang Sicong Kang Fuquan Wang Haixu Zhang Man Xu Wei Wang Jinrui Bai Shaojie Song Qili Dai Yinchang Feng Philip K.Hopke State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and control&Tianjin Key Laboratory of Urban Transport Emission research College of Environmental Science and EngineeringNankai UniversityTianjin 300350China CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health research Tianjin 300350China Beijing Make Environment Science&Technology Co. Ltd.Beijing 100083China Shijiazhuang Environmental Prediction center Shijiazhuang 050022China Department of public Health Sciences University of Rochester School of Medicine and DentistryRochesterNY 14642USA Institute for a Sustainable Environment Clarkson UniversityPotsdamNY 13699USA

Substantial effects of photochemical reaction losses of volatile organic compounds(VOCs)on factor profiles can be investigated by comparing the differences between daytime and nighttime dispersion-normalized VOC data resolved *** speciated VOC data measured in Shijiazhuang,China from May to September 2021 were used to conduct *** mean VOC concentration in the daytime and at nighttime were 32.8 and 36.0 ppbv,*** and aromatics concentrations in the daytime(12.9 and 3.08 ppbv)were lower than nighttime(15.5 and 3.63 ppbv),whereas that of alkenes showed the opposite *** concentration differences between daytime and nighttime for alkynes and halogenated hydrocarbonswere uniformly *** reactivities of the dominant species in factor profiles for gasoline emissions,natural gas and diesel vehicles,and liquefied petroleum gas were relatively low and their profiles were less affected by photochemical *** losses produced a substantial impact on the profiles of solvent use,petrochemical industry emissions,combustion sources,and biogenic emissions where the dominant species in these factor profiles had high *** the profile of biogenic emissions was substantially affected by photochemical loss of isoprene,the low emissions at nighttime also had an important impact on its *** losses of highly active VOC species substantially reduced their concentrations in apportioned factor *** study results were consistent with the analytical results obtained through initial concentration estimation,suggesting that the initial concentration estimation could be the most effective currently availablemethod for the source analyses of active VOCs although with uncertainty.

关键词： Volatile organic compounds Dispersion normalization Photochemical loss Factor profile Positive matrix factorization